Nonparametric inference for the proportionality function in the random censorship model
By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its u...
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Published in: | Journal of nonparametric statistics Vol. 15; no. 2; pp. 151 - 169 |
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01-04-2003
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Abstract | By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its uniform consistency, and obtain a weak convergence result. Furthermore, a confidence band for β( t ), based on the bootstrap, is developed. The results are applied to an actual dataset. |
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AbstractList | By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role in studying aspects of the randomly censored model. We develop an asymptotically efficient nonparametric estimator of β( t ), establish its uniform consistency, and obtain a weak convergence result. Furthermore, a confidence band for β( t ), based on the bootstrap, is developed. The results are applied to an actual dataset. |
Author | Song, Kai-Sheng Laird, Glen Hollander, Myles |
Author_xml | – sequence: 1 givenname: Myles surname: Hollander fullname: Hollander, Myles organization: Department of Statistics and Statistical Consulting Center , Florida State University – sequence: 2 givenname: Glen surname: Laird fullname: Laird, Glen organization: Department of Statistics and Statistical Consulting Center , Florida State University – sequence: 3 givenname: Kai-Sheng surname: Song fullname: Song, Kai-Sheng organization: Department of Statistics and Statistical Consulting Center , Florida State University |
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Cites_doi | 10.2307/2286474 10.1080/02331889808802626 10.1080/02331888808802115 10.1093/biomet/74.4.883 10.1214/aos/1176342705 10.1073/pnas.72.1.20 10.1007/978-1-4612-4348-9 10.2307/2335584 10.1093/biomet/64.2.225 10.1109/TR.1981.5221168 10.1007/978-1-4757-2728-9 10.2307/3314763 10.2307/2287832 |
ContentType | Journal Article |
Copyright | Copyright Taylor & Francis Group, LLC 2003 |
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References | Rudin W. (CIT0018) 1976 Csörgo S. (CIT0008) 1989 Klein J. (CIT0015) 1997 CIT0010 CIT0020 Andersen P. (CIT0001) 1993 CIT0011 Billingsley P. (CIT0003) 1968 Bickel P. (CIT0002) 1993 Csörgo S. (CIT0006) 1983; 18 Gill R. (CIT0012) 1989; 16 Koziol J. (CIT0016) 1976; 63 CIT0014 CIT0013 van der Vaart (CIT0021) 1991; 18 CIT0005 CIT0004 CIT0007 CIT0017 CIT0009 CIT0019 |
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Snippet | By generalizing the proportional hazards model, we introduce a new function β( t ), which we call the proportionality function, and which we show plays a role... |
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SubjectTerms | Nonparametric Estimation Proportional Hazards Model Proportionality Function Random Censorship Model Uniform Convergence Weak Convergence |
Title | Nonparametric inference for the proportionality function in the random censorship model |
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